Evaluating the spatial distribution of water balance in a small watershed,Pennsylvania

A conceptual water‐balance model was modified from a point application to be distributed for evaluating the spatial distribution of watershed water balance based on daily precipitation, temperature and other hydrological parameters. The model was calibrated by comparing simulated daily variation in soil moisture with field observed data and results of another model that simulates the vertical soil moisture flow by numerically solving Richards' equation. The impacts of soil and land use on the hydrological components of the water balance, such as evapotranspiration, soil moisture deficit, runoff and subsurface drainage, were evaluated with the calibrated model in this study. Given the same meteorological conditions and land use, the soil moisture deficit, evapotranspiration and surface runoff increase, and subsurface drainage decreases, as the available water capacity of soil increases. Among various land uses, alfalfa produced high soil moisture deficit and evapotranspiration and lower surface runoff and subsurface drainage, whereas soybeans produced an opposite trend. The simulated distribution of various hydrological components shows the combined effect of soil and land use. Simulated hydrological components compare well with observed data. The study demonstrated that the distributed water balance approach is efficient and has advantages over the use of single average value of hydrological variables and the application at a single point in the traditional practice. Copyright © 2000 John Wiley & Sons, Ltd.     

Assessing the Sensitivity of a Model of Runoff Formation in the Ussuri River Basin

A physically based model of runoff formation with daily resolution has been developed for the upper part of the Ussuri basin with an area of 24400 km² based on ECOMAG hydrological modeling platform. Two versions of the hydrological model have been studied: (1) a crude version with the spatial schematization of the drainage area and river network based on DEM 1 × 1 km with the use of soil and landscape maps at a scale of 1: 2500000 and (2) a detailed version with DEM 80 × 80 m and soil and landscape maps of the scale of 1: 100000. Each version of the model has been tested for two variants of meteorological inputs: (1) meteorological forcing data (temperature, air humidity, precipitation) at eight weather stations and (2) with the involvement of additional data on precipitation collected at 15 gages in the basin. The model has been calibrated and validated over a 34-year period (1979–2012) with the use of runoff data for the Ussuri R. and its tributaries. The results of numerical experiments for assessing the sensitivity of model hydrological response to the spatial resolution of land surface characteristics and the density of precipitation gaging stations are discussed.     

Hydrological field data from a modeller's perspective: Part 2: process‐based evaluation of model hypotheses

The current generation of hydrological models has been widely criticized for their inability to adequately simulate hydrological processes. In this study, we evaluate competing model representations of hydrological processes with respect to their capability to simulate observed processes in the Mahurangi River basin in Northland, New Zealand. In the first part of this two‐part series, the precipitation, soil moisture, and flow data in the Mahurangi were used to estimate the dominant hydrological processes and explore several options for their suitable mathematical representation. In this paper, diagnostic tests are applied to gain several insights for model selection. The analysis highlights dominant hydrological processes (e.g. the importance of vertical drainage and baseflow compared to sub‐surface stormflow), provides guidance for the choice of modelling approaches (e.g. implicitly representing sub‐grid heterogeneity in soils), and helps infer appropriate values for model parameters. The approach used in this paper demonstrates the benefits of flexible model structures in the context of hypothesis testing, in particular, supporting a more systematic exploration of current ambiguities in hydrological process representation. The challenge for the hydrological community is to make better use of the available data, not only to estimate parameter values but also to diagnostically identify more scientifically defensible model structures. Copyright © 2010 John Wiley & Sons, Ltd.     

Challenges of hydrological analysis for water resource development in semi-arid mountainous regions: case study in Iran

Abstract

This study modified the BTOPMC (Block-wise TOPMODEL with the Muskingum-Cunge routing method) distributed hydrological model to make it applicable to semi-arid regions by introducing an adjustment coefficient for infiltration capacity of the soil surface, and then applied it to two catchments above the dams in the Karun River basin, located in semi-arid mountain ranges in Iran. The application results indicated that the introduced modification improved the model performance for simulating flood peaks generated by infiltration excess overland runoff at a daily time scale. The modified BTOPMC was found to fulfil the need to reproduce important signatures of basin hydrology for water resource development, such as annual runoff, seasonal runoff, low flows and flood flows. However, it was also very clear that effective model use was significantly constrained by the scarcity of ground-gauged precipitation data. Considerable efforts to improve the precipitation data acquisition should precede water resource development planning.

Editor D. Koutsoyiannis     

The assessment of surface water resources for the semi‐arid Yongding River Basin from 1956 to 2000 and the impact of land use change

The assessment of surface water resources (SWRs) in the semi‐arid Yongding River Basin is vital as the basin has been in a continuous state of serious water shortage over the last 20 years. In this study, the first version of the geomorphology‐based hydrological model (GBHM) has been applied to the basin over a long period of time (1956–2000) as part of an SWR assessment. This was done by simulating the natural hydrological processes in the basin. The model was first evaluated at 18 stream gauges during the period from 1990 to 1992 to evaluate both the daily streamflows and the annual SWRs using the land use data for 1990. The model was further validated in 2000 with the annual SWRs at seven major stream gauges. Second, the verified model was used in a 45‐year simulation to estimate the annual SWRs for the basin from 1956 to 2000 using the 1990 land use data. An empirical correlation between the annual precipitation and the annual SWRs was developed for the basin. Spatial distribution of the long‐term mean runoff coefficients for all 177 sub‐basins was also achieved. Third, an additional 10‐year (1991–2000) simulation was performed with the 2000 land use data to investigate the impact of land use changes from 1990 to 2000 on the long‐term annual SWRs. The results suggest that the 10‐year land use changes have led to a decrease of 8·3 × 10⁷ m³ (7·9% of total) for the 10‐year mean annual SWRs in the simulation. To our knowledge, this work is the first attempt to assess the long‐term SWRs and the impact of land use change in the semi‐arid Yongding River Basin using a semi‐distributed hillslope hydrological model. Copyright © 2010 John Wiley & Sons, Ltd.     

Preliminary streamflow data analyses prior to water resources planning study / Analyses préliminaires des données de débit en vue d'une étude de planification des ressources en eau

Abstract

The analysis and use of hydrological data for decision making in water resources planning and management can only be meaningful if the data possess the appropriate characteristics. In general, it is customary that data being analysed are consistent, free of trend and constituting a stochastic process whose random component is described by an appropriate probability distribution hypothesis. This paper describes, using hypothetical numerical examples where possible, some of the commonly used tests for establishing the presence or otherwise of these attributes in hydrological data series. The tests were then applied to actual streamflow data records from seven sites, in Iran and England, which formed the basis of an extensive water resources planning study carried out recently. In general, the data from all seven sites possessed the right attributes, which made their use in the wider water resources planning study straightforward.     

Hydrological field data from a modeller's perspective: Part 1. Diagnostic tests for model structure

Hydrological scientists develop perceptual models of the catchments they study, using field measurements and observations to build an understanding of the dominant processes controlling the hydrological response. However, conceptual and numerical models used to simulate catchment behaviour often fail to take advantage of this knowledge. It is common instead to use a pre‐defined model structure which can only be fitted to the catchment via parameter calibration. In this article, we suggest an alternative approach where different sources of field data are used to build a synthesis of dominant hydrological processes and hence provide recommendations for representing those processes in a time‐stepping simulation model. Using analysis of precipitation, flow and soil moisture data, recommendations are made for a comprehensive set of modelling decisions, including Evapotranspiration (ET) parameterization, vertical drainage threshold and behaviour, depth and water holding capacity of the active soil zone, unsaturated and saturated zone model architecture and deep groundwater flow behaviour. The second article in this two‐part series implements those recommendations and tests the capability of different model sub‐components to represent the observed hydrological processes. Copyright © 2010 John Wiley & Sons, Ltd.     

Some aspects of the HAPEX-MOBILHY programme: The data base and the modelling strategy

The main thrust of the HAPEX-MOBILHY experiment was towards investigating techniques involved in integrating the turbulent surface fluxes measured at local sites to a larger scale approaching that used in general circulation models.Some aspects of the field data collected at various times and spatial scales are presented. Annual cycle of the soil moisture at many sites is discussed in relation with outputs of a large scale hydrological model. At shorter time scales, the spatial variability of surface energy partition is examined with regard to spatial contrasts in albedo, surface roughness and plant properties related to the two main vegetation classes found in the HAPEX square: A pine forest and the nearby agricultural area.Finally, examples of daily spatial integration with an atmospheric mesoscale model including a comprehensive treatment of land surface processes are presented.     

Soil infiltration processes of different underlying surfaces in the permafrost region on the Tibetan Plateau

ABSTRACT

Soil infiltration processes were evaluated under field conditions by double-ring infiltrometers with different underlying surfaces in permafrost regions of the Tibetan Plateau. The results show that initial infiltration rates, stable soil infiltration rates and cumulative soil infiltration are strongly dependent on the underlying surface types, with the highest initial and stable soil infiltration rates in the alpine desert steppe, and the lowest in alpine meadow. The effects of soil moisture and texture on infiltration processes were also assessed. Within the same underlying surfaces, the values of infiltration parameters increased with the amount of vegetation cover, while soil moisture and soil infiltration rates displayed opposing trends, with fitting slopes of ?0.03 and ?0.01 for the initial and stable soil infiltration rates, respectively. The accuracies of the five models in simulating soil infiltration rates and seven models in predicting cumulative infiltration rates were evaluated against data generated from field experiments at four sites. Based on a comparative analysis, the Horton model provided the most complete understanding of the underlying surface effects on soil infiltration processes. Altogether, these findings show that different underlying surfaces can alter soil infiltration processes. This study provides a useful reference for understanding the parameterization of land surface processes for simulating changes in hydrological processes under global warming conditions in the permafrost region on the Tibetan Plateau.     

A MATLAB implementation of TOPMODEL

The MATLAB SIMULINK programming language is applied to the TOPMODEL rainfall–runoff model. SIMULINK requires a good recognition of model dynamics, which has been achieved here in a version based on the first TOPMODEL (Beven and Kirkby, 1979). Introducing the topographic index distribution in a vector form allows the generalization and simplification of the SIMULINK structure. The SIMULINK version of TOPMODEL has a very easy to understand graphical representation, which shows, in a straightforward way, all the physical interactions that take place in the model. Moreover, owing to its modular structure it is easy to add new and/or develop old submodels, depending on the available data and the goal of the modelling. In the example given here TOPMODEL was extended by two submodels representing the soil moisture and evaporation distribution in the catchment. Preparation of the data and presentation of the results is done in MATLAB. Discharge predictions and spatial patterns of hydrological response are demonstrated for a separate validation period. © 1997 John Wiley & Sons, Ltd.     

Modelling Canadian prairie wetland hydrology using a semi‐distributed streamflow model

A hydrological model (SLURP) that was designed for simulating hydrological processes taking place in large river basins was, with minimal modification, used successfully to simulate water level variations over a 28‐year period (1969–1996) for a 3‐ha prairie wetland in Saskatchewan. The model calculates a water balance based on precipitation, snowmelt, evaporation, surface runoff and subsurface flow on a daily time‐step. The model was first calibrated for two periods (1969–1973 for cropland and 1987–1990 for grassland), then it was applied to records outside the calibration periods. The model reproduced the wetland water level variations during a 28‐year period with good accuracy. The wetland water levels were most sensitive to the infiltration coefficient of surface soil under frozen conditions and to maximum soil moisture storage. The applicability of the model and the calibrated parameters to a smaller wetland, with an area of 0·24 ha, was examined. This simulation indicated that scale effects are important, probably largely in relation to snow redistribution by wind. Copyright © 2000 John Wiley & Sons, Ltd.     

Observational and predictive uncertainties for multiple variables in a spatially distributed hydrological model

In this study, uncertainty in model input data (precipitation) and parameters is propagated through a physically based, spatially distributed hydrological model based on the MIKE SHE code. Precipitation uncertainty is accounted for using an ensemble of daily rainfall fields that incorporate four different sources of uncertainty, whereas parameter uncertainty is considered using Latin hypercube sampling. Model predictive uncertainty is assessed for multiple simulated hydrological variables (discharge, groundwater head, evapotranspiration, and soil moisture). Utilizing an extensive set of observational data, effective observational uncertainties for each hydrological variable are assessed. Considering not only model predictive uncertainty but also effective observational uncertainty leads to a notable increase in the number of instances, for which model simulation and observations are in good agreement (e.g., 47% vs. 91% for discharge and 0% vs. 98% for soil moisture). Effective observational uncertainty is in several cases larger than model predictive uncertainty. We conclude that the use of precipitation uncertainty with a realistic spatio‐temporal correlation structure, analyses of multiple variables with different spatial support, and the consideration of observational uncertainty are crucial for adequately evaluating the performance of physically based, spatially distributed hydrological models.     

Simulating pan‐Arctic runoff with a macro‐scale terrestrial water balance model

A terrestrial hydrological model, developed to simulate the high‐latitude water cycle, is described, along with comparisons with observed data across the pan‐Arctic drainage basin. Gridded fields of plant rooting depth, soil characteristics (texture, organic content), vegetation, and daily time series of precipitation and air temperature provide the primary inputs used to derive simulated runoff at a grid resolution of 25 km across the pan‐Arctic. The pan‐Arctic water balance model (P/WBM) includes a simple scheme for simulating daily changes in soil frozen and liquid water amounts, with the thaw–freeze model (TFM) driven by air temperature, modelled soil moisture content, and physiographic data. Climate time series (precipitation and air temperature) are from the National Centers for Environmental Prediction (NCEP) reanalysis project for the period 1980–2001. P/WBM‐generated maximum summer active‐layer thickness estimates differ from a set of observed data by an average of 12 cm at 27 sites in Alaska, with many of the differences within the variability (1σ) seen in field samples. Simulated long‐term annual runoffs are in the range 100 to 400 mm year^?1. The highest runoffs are found across northeastern Canada, southern Alaska, and Norway, and lower estimates are noted along the highest latitudes of the terrestrial Arctic in North America and Asia. Good agreement exists between simulated and observed long‐term seasonal (winter, spring, summer–fall) runoff to the ten Arctic sea basins (r = 0·84). Model water budgets are most sensitive to changes in precipitation and air temperature, whereas less affect is noted when other model parameters are altered. Increasing daily precipitation by 25% amplifies annual runoff by 50 to 80% for the largest Arctic drainage basins. Ignoring soil ice by eliminating the TFM sub‐model leads to runoffs that are 7 to 27% lower than the control run. The results of these model sensitivity experiments, along with other uncertainties in both observed validation data and model inputs, emphasize the need to develop improved spatial data sets of key geophysical quantities (particularly climate time series) to estimate terrestrial Arctic hydrological budgets better. Copyright © 2003 John Wiley & Sons, Ltd.     

A parameter allocation approach for flow simulation using the WetSpa-Python model

Hydrologic models are simplified representations of natural hydrologic systems. Since these models rely on assumptions and simplifications to capture some aspects of hydrological processes, calibration of parameters is unavoidable. However, utilizing the philosophy of a recent modelling framework proposed by Bahremand (2016), we show how calibration of most model parameters can be avoided by allocating or presetting these parameters utilizing knowledge gained from sensitivity analyses, field observations and a priori specifications as a part of a parameter allocation procedure. This paper details the simulation of daily river flow of the Shemshak-Roudak watershed performed using the Python version of the WetSpa model. The WetSpa-Python model is a distributed model of hydrological processes applied at the watershed scale. The model was applied to the Shemshak-Roudak watershed of Iran with parameter allocation. Model calibration involved only two parameters. Straightforward methods were proposed for allocating model parameters, including three baseflow-related parameters and the determination of maximum active groundwater storage using a mass curve technique. Also, the Budyko curve was used to constrain a correction factor for potential evapotranspiration. The WetSpa-Python model was extended to include the influence of snowmelt. A failure to include snow in the hydrological processes of the WetSpa-Python model creates a significant discrepancy between the observed and simulated hydrographs during the spring. The results of daily simulations for 12 years (2002–2014) are in good agreement with observations of discharge (Kling-Gupta Efficiency = 0.84). These results demonstrate that it is feasible to simulate hydrographs with limited calibration given a knowledge of hydrological processes and an understanding of relationships between catchment characteristics and model parameters.     

An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop–soil system: Validation and application

Models for water transfer in the crop–soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop–soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop–soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration.     

Potential of the LASH model for water resources management in data-scarce basins: a case study of the Fragata River basin,southern Brazil

ABSTRACT

The objective of this study was to evaluate, based on a data-scarce basin in southern Brazil, the potential of the Lavras Simulation of Hydrology (LASH) model for estimating daily streamflows, annual streamflow indicators and the flow–duration curve. It was also used to simulate the different runoff components and their consistency with the basin physiographical characteristics. The statistical measures indicated that LASH can be considered suitable according to widely used classifications and when compared with other studies involving hydrological models. LASH also showed satisfactory results for annual indicators, especially for maximum and average annual streamflows, as well as for the flow–duration curve. It was found that the model was consistent with the basin characteristics when simulating runoff components. The results obtained in this study allowed us to conclude that the LASH model has the potential to aid practitioners in water resources management of basins with scarce data and similar soil and land-use conditions.

Editor A. Castellarin; Associate editor Y. Gyasi-Agyei     

Development of a polder module in the SWAT model: SWATpld for simulating polder areas in south‐eastern China

Polders are one of the most common artificial hydrological entities in the plain river network regions of China. Due to enclosed dikes, manual drainage, and irrigation intake operations, polders have had a significant impact on the hydrological processes of these areas. Distributed hydrological models are effective tools to understand and reproduce the hydrological processes of a watershed. To date, however, few models are able to simulate the drainage and irrigation intake interactions of polders at a watershed scale. This study develops a modified version of the Soil and Water Assessment Tool (SWAT) model, which is designed to better represent polders (SWATpld). The SWATpld model simulates drainage and irrigation intake processes by calculating the excess‐water storage in the inner rivers and irrigation schedule for paddy rice in the polder. Both SWAT and SWATpld models were tested for the Liyang watershed. SWATpld outperformed SWAT in simulating the daily discharge and intake of the experimental polder and predicting the monthly peak flow at the outlet of the Liyang watershed, which suggests that the modified model simulates the hydrological responses of the study watershed with polder operations more realistically than the original SWAT model does. Further evaluation at various locations and in various climate conditions would increase the confidence of this model.     

Advancing isotope-enabled hydrological modelling for ungauged calibration of data-scarce humid tropical catchments

Realistic projections of the future climate and how this translates to water availability is crucial for sustainable water resource management. However, data availability constrains the capacity to simulate streamflow and corresponding hydrological processes. Developing more robust hydrological models and methods that can circumvent the need for large amounts of hydro-climatic data is crucial to support water-related decisions, particularly in developing countries. In this study, we use natural isotope tracers in addition to hydro-climate data within a newly developed version of the spatially-distributed J2000iso as an isotope-enabled rainfall-runoff model simulating both water and stable isotope (δ²H) fluxes. We pilot the model for the humid tropical San Carlos catchment (2500 km²) in northeastern Costa Rica, which has limited time series, but spatially distributed data. The added benefit of simulating stable isotopes was assessed by comparing different amounts of observation data using three model calibration strategies (i) three streamflow gauges, (ii) three gauges with stream isotopes and (iii) isotopes only. The J2000iso achieved a streamflow Kling–Gupta efficiency (KGE) of 0.55–0.70 across all the models and gauges, but differences in hydrological process simulations emerged when including stable water isotopes in the rainfall-runoff calibration. Hydrological process simulation varied between the standard J2000 rainfall-runoff model with a high simulated surface runoff proportion of 37% as opposed to the isotope version with 84%–89% simulated baseflow or interflow. The model solutions that used only isotope data for calibration exhibited differences in simulated interflow, baseflow and model performance but captured bulk water balances with a reasonable match between the simulated and observed hydrographs. We conclude that J2000iso has shown the potential to support water balance modelling for ungauged catchments using stable isotope, satellite and global reanalysis data sets.     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.